{"id":"https://openalex.org/W4417355692","doi":"https://doi.org/10.1109/host68814.2026.11604915","title":"ObfusBFA: A Holistic Approach to Safeguarding DNNs From Different Types of Bit-Flip Attacks","display_name":"ObfusBFA: A Holistic Approach to Safeguarding DNNs From Different Types of Bit-Flip Attacks","publication_year":2026,"publication_date":"2026-05-04","ids":{"openalex":"https://openalex.org/W4417355692","doi":"https://doi.org/10.1109/host68814.2026.11604915"},"language":"en","primary_location":{"id":"doi:10.1109/host68814.2026.11604915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/host68814.2026.11604915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.10744","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101273080","display_name":"Xiaobei Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiaobei Yan","raw_affiliation_strings":["Nanyang Technological University,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019692903","display_name":"Han Qiu","orcid":"https://orcid.org/0000-0003-2678-8070"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Qiu","raw_affiliation_strings":["Tsinghua University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028270700","display_name":"Tianwei Zhang","orcid":"https://orcid.org/0000-0001-6777-1668"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Tianwei Zhang","raw_affiliation_strings":["Nanyang Technological University,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"344","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9542999863624573,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9542999863624573,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11424","display_name":"Security and Verification in Computing","score":0.014499999582767487,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.011900000274181366,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7049000263214111},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5281999707221985},{"id":"https://openalex.org/keywords/codebase","display_name":"Codebase","score":0.5131000280380249},{"id":"https://openalex.org/keywords/obfuscation","display_name":"Obfuscation","score":0.4943999946117401},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.47940000891685486},{"id":"https://openalex.org/keywords/threat-model","display_name":"Threat model","score":0.43459999561309814},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38580000400543213},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.382999986410141}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.794700026512146},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7049000263214111},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5281999707221985},{"id":"https://openalex.org/C51929080","wikidata":"https://www.wikidata.org/wiki/Q2425187","display_name":"Codebase","level":3,"score":0.5131000280380249},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.47940000891685486},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.43459999561309814},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4169999957084656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.382999986410141},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C2776743756","wikidata":"https://www.wikidata.org/wiki/Q5097921","display_name":"Safeguarding","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C63361517","wikidata":"https://www.wikidata.org/wiki/Q5645805","display_name":"Hamming weight","level":5,"score":0.2777999937534332},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.26510000228881836},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.250900000333786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/host68814.2026.11604915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/host68814.2026.11604915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2506.10744","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.10744","pdf_url":"https://arxiv.org/pdf/2506.10744","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.10744","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.10744","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.10744","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.10744","pdf_url":"https://arxiv.org/pdf/2506.10744","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Bit-flip":[0],"attacks":[1,50,103],"(BFAs)":[2],"represent":[3],"a":[4,14,38,192],"serious":[5],"threat":[6],"to":[7,67,89,114,124,152,154],"Deep":[8],"Neural":[9],"Networks":[10],"(DNNs),":[11],"where":[12,144],"flipping":[13],"small":[15],"number":[16],"of":[17,86,138],"bits":[18,127],"in":[19,37],"the":[20,29,34,72,95,101,141,145,148,166,178],"model":[21,30,35,74,96,167],"parameters":[22],"or":[23,32,80],"binary":[24],"code":[25],"can":[26,163],"significantly":[27,176],"degrade":[28],"accuracy":[31,168],"mislead":[33],"prediction":[36],"desired":[39],"way.":[40],"Existing":[41],"defenses":[42],"exclusively":[43],"focus":[44],"on":[45],"protecting":[46],"models":[47],"for":[48,56,112,195],"specific":[49],"and":[51,64,76,116,128,172,187],"platforms,":[52],"while":[53,175],"lacking":[54],"effectiveness":[55],"other":[57],"scenarios.":[58],"We":[59,120,132],"propose":[60],"ObfusBFA,":[61],"an":[62],"efficient":[63],"holistic":[65],"methodology":[66],"mitigate":[68],"BFAs":[69],"targeting":[70],"both":[71],"high-level":[73],"weights":[75],"low-level":[77],"codebase":[78],"(executables":[79],"shared":[81],"libraries).":[82],"The":[83,158],"key":[84],"idea":[85],"ObfusBFA":[87,134,162],"is":[88],"introduce":[90],"random":[91,105],"dummy":[92],"operations":[93],"during":[94],"inference,":[97],"which":[98],"effectively":[99],"transforms":[100],"delicate":[102],"into":[104],"bit":[106,150],"flips,":[107],"making":[108,190],"it":[109,183,191],"much":[110],"harder":[111],"attackers":[113],"pinpoint":[115],"exploit":[117],"vulnerable":[118],"bits.":[119],"design":[121],"novel":[122],"algorithms":[123],"identify":[125],"critical":[126],"insert":[129],"obfuscation":[130],"operations.":[131],"evaluate":[133],"against":[135],"different":[136],"types":[137],"attacks,":[139],"including":[140],"adaptive":[142],"scenarios":[143],"attacker":[146],"increases":[147],"flip":[149],"budget":[151],"attempt":[153],"circumvent":[155],"our":[156],"defense.":[157],"results":[159],"show":[160],"that":[161],"consistently":[164],"preserve":[165],"across":[169],"various":[170],"datasets":[171],"DNN":[173],"architectures":[174],"reducing":[177],"attack":[179],"success":[180],"rates.":[181],"Additionally,":[182],"introduces":[184],"minimal":[185],"latency":[186],"storage":[188],"overhead,":[189],"practical":[193],"solution":[194],"real-world":[196],"applications.":[197]},"counts_by_year":[],"updated_date":"2026-07-17T05:52:16.776730","created_date":"2025-10-10T00:00:00"}
